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Title: Short Distance of Nuclei - Mining the Wealth of Existing Jefferson Lab Data - Final Report

Over the last fifteen years of operation, the Jefferson Lab CLAS Collaboration has performed many experiments using nuclear targets. Because the CLAS detector has a very large acceptance and because it used a very open (i.e., nonspecific) trigger, there is a vast amount of data on many different reaction channels yet to be analyzed. The goal of the Jefferson Lab Nuclear Data Mining grant was to (1) collect the data from nuclear target experiments using the CLAS detector, (2) collect the associated cuts and corrections used to analyze that data, (3) provide non-expert users with a software environment for easy analysis of the data, and (4) to search for interesting reaction signatures in the data. We formed the Jefferson Lab Nuclear Data Mining collaboration under the auspices of this grant. The collaboration successfully carried out all of our goals. Dr. Gavalian, the data mining scientist, created a remarkably user-friendly web-based interface to enable easy analysis of the nuclear-target data by non-experts. Data from many of the CLAS nuclear target experiments has been made available on servers at Old Dominion University. Many of the associated cuts and corrections have been incorporated into the data mining software. The data mining collaboration wasmore » extraordinarily successful in finding interesting reaction signatures in the data. Our paper Momentum sharing in imbalanced Fermi systems was published in Science. Several analyses of CLAS data are continuing and will result in papers after the end of the grant period. We have held several analysis workshops and have given many invited talks at international conferences and workshops related to the data mining initiative. Our initiative to maximize the impact of data collected with CLAS in the 6-GeV era was very successful. During the hiatus between the end of 6-GeV experiments and the beginning of 12-GeV experiments, our collaboration and the physics community at large benefited tremendously from the Jefferson Lab Nuclear Data Mining effort.« less
ORCiD logo [1] ;  [1]
  1. Old Dominion Univ., Norfolk, VA (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Technical Report
Research Org:
Old Dominion Univ., Norfolk, VA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26)
Contributing Orgs:
Thomas Jefferson National Accelerator Facility, Tel Aviv University, MIT, Penn State U, Florida International U
Country of Publication:
United States
73 NUCLEAR PHYSICS AND RADIATION PHYSICS data mining; nuclear structure; short range correlations; electron scattering